A data-mining approach to understanding the impact of multi-doping on the ionic transport mechanism of solid electrolytes materials: the case of dual-doped Ga0.15/Scy Li7La3Zr2O12

Cortés, Henry A.; Bonilla, Mauricio R.; Früchtl, Herbert; van Mourik, Tanja; Carrasco, Javier; Akhmatskaya, Elena

doi:10.1039/d3ta07036k

Cited by 1 publication

(2 citation statements)

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“…Due to the discrete nature of the generated trajectories and technicalities of the k-means clustering approach, it is difficult to unequivocally establish the start and end points of ionic diffusion paths; thus, an arbitrary but physically reasonable threshold distance of 0.5 Å from the midpoint of the vibrational centers has been adopted here to define the extremities of diffusive trajectories. It is noted that a similar, although not identical, k-means clustering algorithm for unsupervised identification of ionic hops was recently developed by others and applied to the study of an oxide solid electrolyte …”

Section: Resultsmentioning

confidence: 99%

“…It is noted that a similar, although not identical, k-means clustering algorithm for unsupervised identification of ionic hops was recently developed by others and applied to the study of an oxide solid electrolyte. 30 An illustrative example of our method for identification of vibrational centers and ionic diffusion paths is shown in Figure 2a. Therein, two vibrational centers with a highly confident average silhouette coefficient value of 0.88 (green and yellow points) are depicted along with the ionic diffusion path (blue points) that connects them.…”

Section: K-meansmentioning

confidence: 99%

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How Concerted Are Ionic Hops in Inorganic Solid-State Electrolytes?

López,

Rurali,

Cazorla

2024

J. Am. Chem. Soc.

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Despite being fundamental to the understanding of solid-state electrolytes (SSEs), little is known on the degree of coordination between mobile ions in diffusive events, thus hindering a detailed comprehension and possible rational design of SSEs. Here, we introduce an unsupervised k-means clustering approach that is able to identify ion-hopping events and correlations between many mobile ions and apply it to a comprehensive ab initio MD database comprising several families of inorganic SSEs and millions of ionic configurations. It is found that despite two-body interactions between mobile ions being the largest, higher-order n-ion (2 < n) correlations are most frequent. Specifically, we prove a general exponential decaying law for the probability density function governing the number of concerted mobile ions. For the particular case of Li-based SSEs, it is shown that the average number of correlated mobile ions amounts to 10 ± 5 and that this result is practically independent of the temperature. Interestingly, our data-driven analysis reveals that fast-ionic diffusion strongly and positively correlates with ample hopping lengths and long hopping spans but not with high hopping frequencies and short interstitial residence times. Finally, it is shown that neglection of many-ion correlations generally leads to a modest overestimation of the hopping frequency that roughly is proportional to the average number of correlated mobile ions.

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Section: Resultsmentioning

confidence: 99%

Section: K-meansmentioning

confidence: 99%